Deep neural network for pixel-level electromagnetic particle identification in the MicroBooNE liquid argon time projection chamber
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Summary
The first demonstration of a network's validity on real LArTPC data using MicroBooNE collection plane images is shown and it is shown that the network design, training techniques, and software tools developed to train this network are valid.
- Type
- article
- Published
- 2018-08-22
- Cited by
- 72
- References
- 36
- Access
- Open access
- OpenAlex
- https://openalex.org/W2888500435
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:52068044
Keywords
Time projection chamber, Particle identification, Pixel, Identification (biology), Artificial neural network
References
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- Background rejection in NEXT using deep neural networks
- Deep Learning and Data Labeling for Medical Applications
- Convolutional neural networks applied to neutrino events in a liquid argon time projection chamber
- Design and construction of the MicroBooNE detector
- Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC
- The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector
- Road Extraction by Deep Residual U-Net
- Ionization electron signal processing in single phase LArTPCs. Part I. Algorithm Description and quantitative evaluation with MicroBooNE simulation
- Ionization electron signal processing in single phase LArTPCs. Part II. Data/simulation comparison and performance in MicroBooNE
- Michel electron reconstruction using cosmic-ray data from the MicroBooNE LArTPC
- Machine learning at the energy and intensity frontiers of particle physics
Cited by
- Lorentz Boost Networks: autonomous physics-inspired feature engineering
- Timing and characterization of shaped pulses with MHz ADCs in a detector system: a comparative study and deep learning approach
- Scalable Deep Convolutional Neural Networks for Sparse, Locally Dense Liquid Argon Time Projection Chamber Data
- Searching for boosted dark matter via dark-photon bremsstrahlung
- End-to-End Jet Classification of Quarks and Gluons with the CMS Open Data
- Where are we with light sterile neutrinos?
- Context-enriched identification of particles with a convolutional network for neutrino events
- New Technologies for Discovery
- Novel tracking approach based on fully-unsupervised disentanglement of the geometrical factors of variation
- Low energy muon neutrino reconstruction in MicroBooNE
- Reconstruction and measurement of 𝒪(100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC
- The Short-Baseline Neutrino Program at Fermilab
- Accelerating Deep Neural Networks for Real-time Data Selection for High-resolution Imaging Particle Detectors
- Enhancing neutrino event reconstruction with pixel-based 3D readout for liquid argon time projection chambers
- Vertex-finding and reconstruction of contained two-track neutrino events in the MicroBooNE detector
- First measurement of electron neutrino scattering cross section on argon
- FPGA implementation of neural network accelerator for pulse information extraction in high energy physics
- New opportunities at the next-generation neutrino experiments I: BSM neutrino physics and dark matter
- Report from the A.I. For Nuclear Physics Workshop.
- Benefits of MeV-scale reconstruction capabilities in large liquid argon time projection chambers
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